Scipy.optimize.linprog : Value error - Invalid input

Question

I'm trying to Solve a little probleme just to otpimize some units production in a game, where Alpha is a variety coefficient (it sets how the variable can differ from each other) :

import numpy as np
import scipy.optimize as opti
alpha = 0.05
C = np.array([-1,-1,-1,-1,-15,-3,-3,-4,0,0,0,0,0,0])
B = np.array([1600,0,0,0,0,0,0,0,0,0,0,0,0,0])
MatriceC = np.array([\
np.array([14-((1-alpha)*8),7-((1-alpha)*8),7-((1-alpha)*25),18-((1- 
alpha)*12),30-((1-alpha)*30),40-((1-alpha)*40),18-((1-alpha)*1),76-((1- 
alpha)*16),-1,0,0,0,0,0]),\
np.array([14-((1+alpha)*8),7-((1+alpha)*8),7-((1+alpha)*25),18- 
((1+alpha)*12),30-((1+alpha)*30),40-((1+alpha)*40),18-((1+alpha)*1),76- 
((1+alpha)*16),0,-1,0,0,0,0])*(-1),\
np.array([14-((1-alpha)*30),7-((1-alpha)*2),7-((1-alpha)*13),18-((1- 
alpha)*7),30-((1-alpha)*30),40-((1-alpha)*40),18-((1-alpha)*24),76-((1- 
alpha)*56),0,0,-1,0,0,0]),\
np.array([14-((1+alpha)*30),7-((1+alpha)*2),7-((1+alpha)*13),18- 
((1+alpha)*7),30-((1+alpha)*30),40-((1+alpha)*40),18-((1+alpha)*24),76- 
((1+alpha)*56),0,0,0,-1,0,0])*(-1),\
np.array([8-((1-alpha)*30),8-((1-alpha)*2),25-((1-alpha)*13),12-((1- 
alpha)*7),30-((1-alpha)*30),40-((1-alpha)*40),1-((1-alpha)*24),16-((1- 
alpha)*56),0,0,0,0,-1,0]),\
np.array([8-((1+alpha)*30),8-((1+alpha)*2),25-((1+alpha)*13),12- 
((1+alpha)*7),30-((1+alpha)*30),40-((1+alpha)*40),1-((1+alpha)*24),16- 
((1+alpha)*56),0,0,0,0,0,-1])*(-1)])
#print(help(opti.linprog))
print(np.shape(MatriceC))
print(np.shape(B))
opti.linprog(C,A_eq=MatriceC,b_eq=B) #This causes the error...

And I get as an output :

(6, 14)
(14,)
ValueError: Invalid input for linprog with method = 'simplex'.  The number 
of rows in A_eq must be equal to the number of values in b_eq

Considering the shape of the matrix I get. I don't understand what I'm doing wrong.

PS :

I have tried adding

MatriceC = MatriceC.T

Just before the linprog call and it stills outpout the same error. It did change the (6, 14) shape into (14, 6) (well it's logical)

Answer 1

Transponse your MatriceC with MatriceC.T before passing it to linprog

linprog according to their doc:

Minimize: c^T * x

Subject to: A_ub * x <= b_ub A_eq * x == b_eq

In order to satisfy the above equation, the matrices' dimension should conform to each other. Read about Matrix Multiplication .